The objective of this study was to develop a model to estimate the axle torque (AT) of a tractor using an artificial neural network (ANN) based on a relatively low-cost sensor. ANN has proven to be useful in the case of nonlinear analysis, and it can be applied to consider nonlinear variables such as soil characteristics, unlike studies that only consider tractor major parameters, thus model performance and its implementation can be extended to a wider range. https://www.selleckchem.com/products/ipi-549.html In this study, ANN-based models were compared with multiple linear regression (MLR)-based models for performance verification. The main input data were tractor engine parameters, major tractor parameters, and soil physical properties. Data of soil physical properties (i.e., soil moisture content and cone index) and major tractor parameters (i.e., engine torque, engine speed, specific fuel consumption, travel speed, tillage depth, and slip ratio) were collected during a tractor field experiment in four Korean paddy fields. The collected soil physical properties and major tractor parameter data were used to estimate the AT of the tractor by the MLR- and ANN-based models 250 data points were used for developing and training the model were used, the 50 remaining data points were used to test the model estimation. The AT estimated with the developed MLR- and ANN-based models showed agreement with actual measured AT, with the R2 value ranging from 0.825 to 0.851 and from 0.857 to 0.904, respectively. These results suggest that the developed models are reliable in estimating tractor AT, while the ANN-based model showed better performance than the MLR-based model. This study can provide useful results as a simple method using ANNs based on relatively inexpensive sensors that can replace the existing complex tractor AT measurement method is emphasized.The intake of hesperidin-rich sources, mostly found in orange juice, can decrease cardiometabolic risk, potentially linked to the gut microbial phase-II hesperetin derivatives. However, the low hesperidin solubility hampers its bioavailability and microbial metabolism, yielding a high inter-individual variability (high vs. low-producers) that prevents consistent health-related evidence. Contrarily, the human metabolism of (lemon) eriocitrin is hardly known. We hypothesize that the higher solubility of (lemon) eriocitrin vs. (orange) hesperidin might yield more bioavailable metabolites than hesperidin. A randomized-crossover human pharmacokinetic study (n = 16) compared the bioavailability and metabolism of flavanones from lemon and orange extracts and postprandial changes in oxidative, inflammatory, and metabolic markers after a high-fat-high-sugars meal. A total of 17 phase-II flavanone-derived metabolites were identified. No significant biomarker changes were observed. Plasma and urinary concentrations of all metabolites, including hesperetin metabolites, were higher after lemon extract intake. Total plasma metabolites showed significantly mean lower Tmax (6.0 ± 0.4 vs. 8.0 ± 0.5 h) and higher Cmax and AUC values after lemon extract intake. We provide new insights on hesperetin-eriodictyol interconversion and naringenin formation from hesperidin in humans. Our results suggest that regular consumption of a soluble and eco-friendly eriocitrin-rich lemon extract could provide a circulating concentration metabolites threshold to exert health benefits, even in the so-called low-producers.Timing of micronutrient demand and acquisition by maize (Zea mays L.) is nutrient specific and associated with key vegetative and reproductive growth stages. The objective of this study was to determine the fate of foliar-applied B, Fe, Mn, Zn, and Fe/Zn together, evaluate the effect of foliar micronutrients applied at multiple rates and growth stages on maize grain yield, and determine their apparent nutrient recovery efficiency (ANR). Five Randomized Complete Block Design (RCBD) experiments were conducted in 2014 and 2015 at five locations across Nebraska. Total dry matter was collected at 5-6 stages, and separated into leaves, stalk, and reproductive tissue as appropriate to determine micronutrient uptake, partitioning, and translocation. Foliar B, Mn, Zn, and Fe/Zn had no effect on grain yield for most application time by rate levels, though, at the foliar Mn site, there was a 19% yield increase due to a V18 application of 0.73 kg Mn ha-1 which corresponded with reduced Mn uptake in maize grown in controlc micronutrients, track the fate of foliar-applied micronutrients, and describe the variable effect of foliar-applied micronutrients on grain yield.Kelch-like ECH-associated protein 1 (KEAP1)-nuclear factor E2-related factor 2 (NRF2) is the key antioxidant system in animals. In a previous study, we identified a probable KEAP1 ortholog in rice, OsKEAP1, and demonstrated that the downregulation of OsKEAP1 could alter the redox system and impair plant growth, as well as increase the susceptibility to abscisic acid (ABA) in seed germination. However, no NRF2 orthologs have been identified in plants and the mechanism underlying the phenotype changes of downregulated oskeap1 mutants is yet unknown. An in silico search showed that OsABI5 is the gene that encodes a protein with the highest amino acid identity score (38.78%) to NRF2 in rice. In this study, we demonstrated that, via yeast two-hybrids analysis and bimolecular fluorescence complementation assays, OsKEAP1 interacted with OsABI5 via its Kelch repeat domain in the nucleus. In germinating seeds, the expression of OsKEAP1 was significantly downregulated in oskeap1-1 (39.5% that of the wild-type (WT)) andvia regulating OsABI5, which is the key player in the ABA response. In-depth analyses of the components and their action mode of the KEAP1-NRF2 and ABA signaling pathways suggested that OsKEAP1 likely formed a complex with OsABI5 and OsKEG, and OsABI5 was ubiquitinated by OsKEG and subsequently degraded under physiological conditions; meanwhile, under oxidative stress or with increased an ABA level, OsABI5 was released from the complex, phosphorylated, and transactivated the ABA response genes. Therefore, OsKEAP1-OsABI5 bore some resemblance to KEAP1-NRF2 in terms of its function and working mechanism.